One of the key problems that mathematical epidemiology addressed is the optimisation of vaccination strategies, i.e given a finite supply of vaccines, who should be vaccinated to mitigate an epidemic. Previous work has studied vaccination strategies based upon network topology. Vaccination which prioritises nodes of higher degree, i.e. people with a high number of social contacts, is known to lead to better outcomes in comparison with a random vaccination campaign [1]}. Furthermore, it has been shown that vaccination using information beyond the degree can improve upon degree-based strategies [2]}, [3]}. The recent discovery of the role that the Hashimoto non-backtracking matrix [4]}, [5]}, [6]} plays in epidemic processes has led to the use of eigenvalues to rank nodes for prioritisation of vaccination [7]}. The benefit of modelling such strategies is that they provide principles upon which vaccination campaigns can be based with only partial knowledge of the contact network. For example, it can provide theoretical insight into prioritising vaccination for parts of the population with higher than average social connectivity.
